Cloud scheduling and management of energy systems with real-time support. This project aims to research cloud scheduling and management of modern energy systems with real-time communication support. The approach consists of optimisation with balanced benefits for customers, aggregators and network service providers for modern energy systems; real-time communication support for unified energy scheduling and management over many microgrids; and cloud energy scheduling and management with deadline ....Cloud scheduling and management of energy systems with real-time support. This project aims to research cloud scheduling and management of modern energy systems with real-time communication support. The approach consists of optimisation with balanced benefits for customers, aggregators and network service providers for modern energy systems; real-time communication support for unified energy scheduling and management over many microgrids; and cloud energy scheduling and management with deadline guarantee. This project is expected to facilitate increasing deployment of disruptive energy technologies on a massive scale, create opportunities for energy industries, and maintain Australia’s leading position in renewable energy.Read moreRead less
Detection of location significance from quality enhanced trajectory data. This project aims to develop effective and efficient methods to utilise large scale Global Positioning System, route and location data to provide individuals, business, government and social groups, the ability to assess the relative significance of locations and associated services, for use in applications such as transportation, logistics, public safety, tourism and utilities.
In-memory moving objects analytics for real-time business applications. This project aims to develop a novel computing foundation based on in-memory technologies to address significant challenges of big data and location-based business intelligence, building upon the well-recognised research excellence in spatiotemporal data management at the University of Queensland, and HANA, SAP's (Systems, Applications, Products in data processing) new in-memory analytics platform.
Declaration, Exploration, Enhancement and Provenance: The DEEP Approach to Data Quality Management Systems. The project proposes the Declaration, Exploration, Enhancement, Provenance (DEEP) approach to data quality management. The approach adopts a whole-of-data-cycle view towards addressing complex and emerging problems in data quality management and aims to develop novel and comprehensive mechanisms to improve data quality measurement, enforcement and monitoring. Due to the application-centric ....Declaration, Exploration, Enhancement and Provenance: The DEEP Approach to Data Quality Management Systems. The project proposes the Declaration, Exploration, Enhancement, Provenance (DEEP) approach to data quality management. The approach adopts a whole-of-data-cycle view towards addressing complex and emerging problems in data quality management and aims to develop novel and comprehensive mechanisms to improve data quality measurement, enforcement and monitoring. Due to the application-centric nature of DEEP, the outcomes from the project are expected to increase user understanding of data characteristics, improve interpretability of information derived from large, multi-source data sets and contribute to enhancement of data literacy levels in involved user communities. Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE140100215
Funder
Australian Research Council
Funding Amount
$394,752.00
Summary
Searching Activity Trajectories for Intention Oriented Recommendations. The ubiquitous fusion of social network services and Global Positioning System-enabled mobile devices has generated large-scale activity trajectory data representing the footprint of people's daily activities. It presents an unprecedented opportunity to build highly intelligent recommendation systems. Existing approaches that merely focus on the location aspect of trajectories are limited in their ability to understand genui ....Searching Activity Trajectories for Intention Oriented Recommendations. The ubiquitous fusion of social network services and Global Positioning System-enabled mobile devices has generated large-scale activity trajectory data representing the footprint of people's daily activities. It presents an unprecedented opportunity to build highly intelligent recommendation systems. Existing approaches that merely focus on the location aspect of trajectories are limited in their ability to understand genuine preferences from travel histories, due to lack of consideration for activity information as well as the associated semantics and context. This project aims to address these issues and provide effective recommendations by considering both users’ intention and collective behavioural knowledge inferred from activity trajectories.Read moreRead less
Indexing Large Video Databases to Support Efficient Query Processing. This project aims to develop breakthrough database technology that leverages the advances in video data capturing, computer vision based object recognition, multimedia tagging, large scale database systems and parallel processing, to provide the capability of managing massive video data with enriched semantic information and enabling database-like flexible and efficient video information search. It is expected to establish a n ....Indexing Large Video Databases to Support Efficient Query Processing. This project aims to develop breakthrough database technology that leverages the advances in video data capturing, computer vision based object recognition, multimedia tagging, large scale database systems and parallel processing, to provide the capability of managing massive video data with enriched semantic information and enabling database-like flexible and efficient video information search. It is expected to establish a new data management and processing foundation for big video data analytics.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE160100308
Funder
Australian Research Council
Funding Amount
$300,000.00
Summary
Mobile User Modeling for Intelligent Recommendation. This project aims to develop effective and efficient techniques to enable individuals, business and government to better understand and exploit knowledge in human daily activity data and to provide higher quality mobile recommendation services such as personalised trip planning and tourist services. The project intends to develop a mobile user modelling framework which accurately infers mobile users' location-time-dependent interests and spa ....Mobile User Modeling for Intelligent Recommendation. This project aims to develop effective and efficient techniques to enable individuals, business and government to better understand and exploit knowledge in human daily activity data and to provide higher quality mobile recommendation services such as personalised trip planning and tourist services. The project intends to develop a mobile user modelling framework which accurately infers mobile users' location-time-dependent interests and spatial mobility patterns from their daily activity records and social ties in geo-social networks. It then intends to combine this knowledge to build an intelligent recommender system. The project outcomes and techniques could be applied in various location-based services, mobile advertising and marketing.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE120102960
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Revocable multi-dimensional shape-based multimodal hand biometrics for personal identification and verification. This project will investigate a new personal verification system based on hand biometrics. It will make significant improvements by thwarting identity frauds; creating trust in ebanking and epayments; providing social acceptance of biometrics; helping immigration and passport control; and reducing use of plastic cards to safeguard the environment.
Making sense of trajectory data: a database approach. This project investigates new challenges related to providing functionality, flexibility and efficiency for large scale trajectory data management and processing. The expected outcome includes significant technical contributions in novel indexing structures and advanced query processing methods for making better use of rich trajectory data.
Making human place knowledge digestible by computers. This project aims to develop the tools that will enable people to interact intuitively with computers about places and the relations between places. People understand their environment in a different way to computers; they think of places and their relations, while computers use coordinates and maps. People’s interaction with maps is cognitively costly and error-prone, which is becoming untenable in situations needing time-critical decision m ....Making human place knowledge digestible by computers. This project aims to develop the tools that will enable people to interact intuitively with computers about places and the relations between places. People understand their environment in a different way to computers; they think of places and their relations, while computers use coordinates and maps. People’s interaction with maps is cognitively costly and error-prone, which is becoming untenable in situations needing time-critical decision making. The project will revolutionise the design of information services where computers deal with humans and location in time-critical or stressful situations, including emergency calls, disaster response and local search queries. The uptake of this design by industry will lead to economic benefits as well as a safer society living in a smarter environment.Read moreRead less